V6I1-8

8/13/2019 V6I1-8

1/15

8/13/2019 V6I1-8

2/15

Impression Management . Abasyn Journal of Social Sciences Vol. 6 No. 1

Yaqoob Ahmad & Gohar Zaman 92

debt and equity. This value increases or the pie gets bigger and

bigger if and only if there is a change in capital structure. Capital

structure decision maximizes the shareholders wealth andminimizes the weighted cost of capital. As we know that different

firms follow different mix of debt and equity which has given birth

to different capital structure theories.

Modigliani and Miller (1958) were the first to describe

capital structure. According to them capital structure is irrelevant

to the value of the firm which is stated in their first proposition I.

Then after it they gave proposition II but although these theories

are based on some unrealistic assumptions. Later on, different

researches were conducted to find out the determinants of capital

structure and an optimal capital structure. Some of the theories on

capital structure are Static Trade-off theory, Pecking order theory

and Signaling theory.

The study on capital structure in Pakistan was first carried

out by Shah and Hijazi (2004) over the firms listed on Karachi

stock Exchange. The study found some of the determinants of

capital structure which were analyzed in the light of capital

structure theories. This research provided a base to the otherresearches because it was the first ever study over Pakistani listed

firms on KSE. Later, different researches were carried out on

different sectors. The study of Rafiq, Iqbal & Atiq (2008) found

that capital structure is industry specific and it varies from industry

to industry. So we cannot assign industry specific attributes on the

whole industry as it is done by Shah and Hijazi (2004).

A study by Akbar, Ali & Tariq (2009) on determinants of

capital structure for Textile sector of Pakistan was the first study in

this sector. This study took all the firms in the entire textile sector

of Pakistan. Broadly the textile sector is divided into three

branches i.e. Textile Composite, Textile Spinning and Textile

Weaving.

8/13/2019 V6I1-8

3/15



Capital structure decisions can be influenced by the

industry specific variables for which Text Composite sector is

taken as a case study. The aim of this study is to further refine orfind the industry specific variables that can influence capital

structure decision. By analyzing the Textile Composite sector

individually can give better results. It may also address the

shortcomings in the combine analysis.

Research Statement

To determine the capital structure of listed firms in the

textile composite sector of Pakistan

Research Objectives

This study is conducted to find out the determinants of capital

structure for the Textile Composite sector of Pakistan. Following

below are some of the objectives that are aimed to be fulfilled;

To examine the relationship of Tangibility of fixed assetswith leverage.

To find out the relationship of size and leverage of the firm. To find out the relationship of growth and leverage of thefirm. To examine the relationship of profitability with leverage

of the firm.

8/13/2019 V6I1-8

4/15



Literature Review

According to a research by Harris & Raviv (1991) ontheory of capital structure, they stated that leverage is positively

related with firm investment opportunities, size ,fixed assets, non-

debt tax shield, and it has a negative relationship with uniqueness

of the product, advertising expenditures, probability of bankruptcy,

volatility and profitability.

The four variables, tangibility of asset, the market to bookvalue ratio, firm size and profitability have proved to be more

consistent as being correlated with leverage in the previous studies

(see Bradley, Jarrel & kim (1984), Long & Malitz(1985), and

Harris & Raviv(1991).

Similarly G.Rajan & Zingales (1995) in their research titled

as what do we know about capital structure? Some evidence from

international data investigated the determinants of capital structure

choice of public firms in the major industrialized G-7 countries.

They observed that the firms of the G-7 countries posses same

leverage at aggregate level. They found that all the cross sections

are affected by the same factors and this is also consistent with the

past researches. They stated in USA leverage is affected by the

same factors as it is in other countries. They concluded from the

evidence that the theoretical foundations of the observed

correlations are not still resolved.

In another research by Correa, Basso & Nakamura (2007)

who analysed some determinants of capital structure for the largestBrazilian firms using Panel data model for the period ranging from

1999 to 2004 by taking up a sample of 389 firms out of 500 largest

companies.The result showed a negative relationship of leverage

with tangibility of assets, profitability and business industry, while

a positive relation exits between risk and capital origin.

According to a research by Shah & Hijazi (2004) on thedeterminants of capital structure for non financial listed firms on

Karachi Stock Exchange for five years period(1997-2001) using

8/13/2019 V6I1-8

5/15



pooled regression model. They observed a negative relation of

growth and profitability with leverage and a positive realtion of

tangibility of asset and size with leverage.However the relationshipof tangibility and leverage was found to be statistically

insignificant.

In another study by Hijazi & Tariq (2006) who analysed the

determinants of capital structure for Cement sector of Pakistan by

using pooled reggression model for 16 firms out of 22 in the

Cement sector. The result showed that tangibility of asset and

growth is positively related to leverage whereas size and

profitability is negatively related to leverage.

Similarly in another study conducted by Shah & Khan

(2007) found the deteminants of capital structure of KSE listed non

financial firms using fixed effect dummy variable regression bytaking 286 firms from financial sector of Pakistan. The results

demonstrated that tangibility and size is positively related to

leverage whereas growth, non debt tax shield and profitability is

negatively related to the leverage. Tangibility, growth and

profitability were found to be statistically significant while size

and non debt tax shield were statistically insignificant. Earningvolatility has no relation with leverage.

Furthermore Rafiq et al.(2008) found the determinants of

capital structure of the chemical industry of Pakistan using Pooled

reggression model by taking 26 firms out of 39 firms from

chemical sector of Pakistan for the period ranging from 1993-2004.

They found that profitability is negatively related to leverage whilenon-debt tax shield, tangibility of asset, income variation and

growth is positively related to leverage.

According to Sheikh & Wang (2011) who conducted a

research on the determinants of capital structure for firms in the

manufacturing industry of pakistan. The study analyzed 160 firms

which are listed in Karachi stock exchange for a period of five

years (2003-2007) using panel data techniques.The result

8/13/2019 V6I1-8

6/15



suggested that profitability, earning volatility, liquidity and

tangibility are negatively related to leverage. Whereas size is

positively related to leverage. Non-debt tax sheild and growthopportunities are not significantly related to leverage.

Similarly Akbar, Ali & Tariq (2009) conducted a research

on the determinants of capital structure in textile sector of

pakistan. They took four variables named as tangibility of assets,

Growth, firm size and profitability following Rajan & Zingales

(1995). They analyzed 155 listed firms from KSE out of total 167

firms for a period of five years(1999-224) using Pooled

reggression analysis. They found their results consistent with the

previous studies. The research proved a positive relationship of

profitability, tangibility and size.whereas the relationship of

growth with leverage was found to be negative.

Theoretical Framework

Independent varaibles include Tangibility of assets, Size,

Profitability and Growth while Dependant varaible includes

Leverage.

Operational Definitions

Firm specific variables are used namely, Size, Growth,

Tangibility of assets and Profitability. These variables were alsoused by previous studies of Rajan and Zingles (1995), Shah and

Hijazi (2005) and Hijazi and Tariq (2006).This study has used the

Tangibility

Size of the firm

Profitabilit

Growth

Levera e

8/13/2019 V6I1-8

7/15



same variables which were used by Akbar, Ali and Tariq (2009) in

Textile sector. These variables are described below.

Leverage

It is the percentage of total assets financed through debt.

Leverage has been used in this research as the ratio of total

liabilities divided by total assets.

Leverage = Total Liabilities / Total assets

Tangibility of Assets

This study has used Tangibility as the ratio of net fixed assets

divided by total assets.

Tangibility = Net Fixed assets / Total assets

Size

This Research has used size as the natural log of total assets.

Size = Ln (Total assets)

Growth

For this study growth has been defined as the percentage change in

total assets.

Growth = Y2-Y1 / Y1 100

Profitability

This study measures profitability as net profit before taxes are

divided by the total assets.

Profitability = Net profit before taxes / total assets

8/13/2019 V6I1-8

8/15



Hypothesis

Hypothesis 1: A firm with higher percentage of fixed assetswill have a higher Debt ratio.

Hypothesis 2: There is a negative relationship between size andleverage of the firm.

Hypothesis 3: Firm with higher growth rate will have higherleverage.

Hypothesis 4: Firm with higher profitability will have lesserleverage.

Research Methodology

Population

The study targeted all the firms of the textile composite

sector of Pakistan which is the main sub sector in the overall textileindustry. So the phenomenon under study was the whole textile

composite sector of Pakistan. The total number of firms were 50 in

this sector which presented them for the analysis.

Sample

The study started with analyzing all the firms in the textilecomposite sector of Pakistan. Out of 50 firms, 46 firms were

selected for the analysis while 4 firms were excluded due to the

non availability of sufficient data. The data was analyzed for a

period of five years (2005-2009). There were 230 firm-years which

were analyzed during the sample period.

Data Collection

The study used secondary type of data in the overall

analysis. The data which was necessary for calculation purpose

was taken from the publication of State bank of Pakistan named as

Balance Sheet Analysis of Joint Stock Companies Listed on the

Karachi Stock Exchange 2005-2009. The financial data was taken

from the same document for the period ranging from 2005-2009.

8/13/2019 V6I1-8

9/15



Annual reports of the selected firms were also used for data

collection.

Table 1. List of Sampled Firms

S/no Name of Firm S/no Name of Firm

1 Sarhad textile mills limited 24 Sapphire Fibres Ltd.

2 Azgard Nine limited(Legler-

nafees denim mills ltd.)

25 Sapphire Textile Mills Ltd.

3 Blessed textile Ltd. 26 Shams Textile Mills Ltd.

4 Colony Mills Ltd.(Colony

textile mills Ltd)

27 Suraj Cotton Mills Ltd.

5 Faisal spinning mills Ltd. 28 Taj Textile Mills Ltd.

6 Fateh Textile Mills Ltd. 29 Towellers Ltd.

7 Ghazi Fabrics International Ltd 30 Usman Textile Mills Ltd.

8 Gul Ahmad Textile mills Ltd 31 Zahur Cotton Mills Ltd.

9 Husein Industries Ltd 32 (Colony) Thal Textile Mills

Ltd.10 Ishaq Textile Mills Ltd 33 Ahmed Hassan Textile Mills

Ltd.

11 Jubilee Spinning & Weaving

Mills Ltd

34 Artistic Denim Mills Ltd.

12 Kohinoor Industries Ltd. 35 Chenab Ltd.

13 Mahmood Textile Mills Ltd. 36 Dawood Lawrencepur

Tex.Ltd. (Dawod Coton

Mills)

14 Masood Textile Mills Ltd. 37 Fateh Sports Wear Ltd.

15 Mian Textile Industries Ltd. 38 Hala Enterprises Ltd.

16 Mohammad Farooq Textile

Mills Ltd.

39 Hamid Textile Mills Ltd.

17 Mubarak Textile Mills Ltd. 40 International Knitwear Ltd.

18 Nina Industries Ltd. 41 Khyber Textile Mills Ltd.

19 Nishat (Chunian) Ltd. 42 Safa Textiles Ltd.20 Paramount Spinning Mills Ltd. 43 Nishat Mills Ltd.

21 Quetta Textile Mills Ltd. 44 Aruj Garment Accessories

Ltd.

22 Redco Textiles Ltd. 45 Kohinoor Textile Mills Ltd.

23 Reliance Weaving Mills Ltd. 46 The Crescent Textile Mills

Ltd.

8/13/2019 V6I1-8

10/15



The Regression Model

The study used pooled regression model for analysis.

Pooled regression is used in this study just because it accompaniesboth cross sectional and time series data. The model can also be

called as constant co-efficient model. This is called constant-

coefficient because in this model both slopes and intercepts are

assumed to be constant. The assumption of this model is that there

is no significant cross section or time effects.

The equation for our regression model is given below (Balance

Sheet Analysis of Joint Stock Companies Listed on the Karachi

Stock Exchange, 2005-2009, State Bank of Pakistan.)

Where

LG = Leverage

TG = Tangibility

SZ = Size

GT = Growth

PF = Profitability

= error term

Data Analysis & Results

This section contains the results of the descriptive statistics and

regression analysis. Table 1 shows the summary of the descriptive

statistics for the variable values in the sample.

8/13/2019 V6I1-8

11/15



Table 1. Descriptive Statistics

Variables N Minimum Maximum Mean Std. Dev.

Leverage 230 0.109253 1.86468 0.742359 0.293211

Tangibility 230 0.000000 0.908824 0.500628 0.202613

Size 230 3.52342 10.5810 7.46554 1.65824

Growth 230 -74.1503 44097.3 201.789 2907.15

Profitability 230 -0.718831 1.73689 0.0153348 0.148278

To check the presence of multicollinearity among predictor

variables, we checked the Correlation matrix which is given below

in Table 2.

Table 2: Correlation Coefficients

Variables TG SZ GT PF

TG 1

SZ -0.1304 1

GW -0.0005 0.0882 1

PF -0.1418 0.0211 -0.0004 1

From table 2 it can be seen that the highest coefficient is -0.14

between two variables which indicates that there is no

multicollinearity problem among the independent variables. We

used correlation matrix for the identification of multicollinearity. A

coefficient of correlation in excess of 0.8 is considered to pose

serious problems for statistical inference.

Table 3. Regression model summary

R Square Adjusted R Square P-value (F)

0.250399 0.237073 2.42e-13

Table 3 represents the value of R-square ( = .25 or 25%)

which indicates that independent variables such as Tangibility of

assets, size, growth and profitability explains on 25% of variation

in dependent variable i.e. Leverage. The overall model is

8/13/2019 V6I1-8

12/15



significant at 1% level of significance as indicated by the value of

F-statistics.

Table 4: Regression Coefficients & their significanceCoefficient Std. Error t-ratio p-value

Const 1.02691 0.0943933 10.8791

8/13/2019 V6I1-8

13/15

8/13/2019 V6I1-8

14/15



found to be statistically insignificant. Finally, the negative

relationship of profitability with leverage confirms the Pecking

order Theory, however, contradicts the Static Trade off Theory.

References

Akbar, M., Ali, S., & Tariq, F. (2009). The Determinants Of

Capital Structure In The Textile Sector Of Pakistan.

Banking & Economic Review, 1, 15-19.

Balance Sheet Analysis of Joint Stock Companies Listed on theKarachi Stock Exchange, 2005-2009, State Bank of

Pakistan.

Bradley, M., Jarrell, G. A., & Kim, H. H. (1984). On the existance

of an optimal capital structure:Theory and Evidence. The

Journal of Finance, 39(3), 857-878.

Correa, C. A., Basso, L. F., & Nakamura, W. T. (2007). Whatdetermines the capital Structure of the Lagest Brazilian

firms? An Empirical Analysis using panel data.

Grossman, S., & Hart, S. (1980). Corporate fiancial structure and

Managerial incentives.

Harris, M., & Raviv, A. (1990). Capital Structure and the

informational role of the Debt. The Journal of Finance,45(2), 321-349.

Harris, M., & Raviv, A. (1991). The Theory of Capital Structure.

The Journal of Finance, 46(1), 297-355.

Hijazi, S. T., & Tariq, Y. B. (2006). Determinants of capital

structure: A case for Pakistani Cement Industry. The

Lahore Journal Of Economics, 11(1), 63-80.

Italian Trade Commission Karachi, Textile Industry of Pakistan

Report, 2009-2010.

Keown, A. J., Petty, J. W., Scott, D. F., & Martin, J. D. (1998).

Foundations Of Finance(Vol. 2).

Myers, S. C. (1977). Determinants of Corporate Borrowing.

Journal of Financial Economics, 5,2, 147-175.

Rafiq, M., Iqbal, A., & Atiq, M. (2008). The Determinants Of

Capital Structure of The Chemical Industry in Pakistan.

The Lahore Journal of Economics, 139-158.

8/13/2019 V6I1-8

15/15



Rajan, R., & Zingales, L. (1995). What do we know about Capital

Structure? Some evidence from international data. The

Journal of Finance, 50(5), 1421-1460.Ross, S. A., Westerfield, R. W., & Jordan, B. D. (2006).

Fundamentals Of Corporate Finance(7 ed.).

Shah, A., & Hijazi, T. (2004). The Determinants of Capital

Structure of Stock Exchange-listed Non-financial Frims in

Pakistan. The Pakistan Developement Review, 605-618.

Shah, A., & Khan, S. (2007). Determinants of Capital Structure:Evidence from Pakistani Panel Data. International Review

of Business Research Papers, 3(4), 265-282.

Sheikh, N. A., & Wang, Z. (2011). Determinants of Capital

Structure An Empirical study of Firms in Manufacturing

Industry of Pakistan. Managerial Finance, 37 (2), 117-

137.Textile Policy, Ministry of Textile Industry,Government of Pakistan

2009-2014.

Year Book, Government of Pakistan, Ministry of Textile Industry

Islamabad,2007-2008.

Documents

V6I1-8